Search results for: prediction modelling

Authors: M. Sadoughi, R. Ehsani

Abstract:

The aim of the present study is examining the relationship between conceptual organizational culture and the level of tolerance in employees of Islamic Azad University of Shahre Ghods. This research is a correlational and analytic-descriptive one. The samples included 144 individuals. A 24-item standard questionnaire of organizational culture by Cameron and Queen was used in this study. This questionnaire has six criteria and each criterion includes four items that each item indicates one cultural dimension. Reliability coefficient of this questionnaire was normed using Cronbach's alpha of 0.91. Also, the 25-item questionnaire of tolerance by Conor and Davidson was used. This questionnaire is in a five-degree Likert scale form. It has seven criteria and is designed to measure the power of coping with pressure and threat. It has the needed content reliability and its reliability coefficient is normed using Cronbach's alpha of 0.87. Data were analyzed using Pearson correlation coefficient and multivariable regression. The results showed among various dimensions of organizational culture, there is a positive significant relationship between three dimensions (family, adhocracy, bureaucracy) and tolerance, there is a negative significant relationship between dimension of market and tolerance and components of organizational culture have the power of prediction and explaining the tolerance. In this explanation, the component of family is the most effective and the best predictor of tolerance.

Keywords: adhocracy, bureaucracy, organizational culture, tolerance

Procedia PDF Downloads 451

Authors: M. Crozet, D. Roudil, T. Branger, S. Boden, P. Peerani, B. Russell, M. Herranz, L. Aldave de la Heras

Abstract:

The EURATOM work program project INSIDER (Improved Nuclear Site Characterization for Waste minimization in Decommissioning under Constrained Environment) was launched in June 2017. This 4-year project has 18 partners and aims at improving the management of contaminated materials arising from decommissioning and dismantling (D&D) operations by proposing an integrated methodology of characterization. This methodology is based on advanced statistical processing and modelling, coupled with adapted and innovative analytical and measurement methods, with respect to sustainability and economic objectives. In order to achieve these objectives, the approaches will be then applied to common case studies in the form of Inter-laboratory comparisons on matrix representative reference samples and benchmarking. Work Package 6 (WP6) ‘Performance analysis and overall uncertainty’ is in charge of the analysis of the benchmarking on real samples, the organisation of inter-laboratory comparison on synthetic certified reference materials and the establishment of overall uncertainty budget. Assessment of the outcome will be used for providing recommendations and guidance resulting in pre-standardization tests.

Keywords: decommissioning, sampling strategy, research and development, characterization, European project

Procedia PDF Downloads 365

Authors: Hamidoddin Yousife

Abstract:

Drilling optimization requires a prediction of drilling rate of penetration (ROP) since it provides a significant reduction in drilling costs. There are several factors that can have an impact on the ROP, both controllable and uncontrollable. Numerous drilling penetration rate models have been considered based on drilling parameters. This papers considered the effect of proper drilling parameter selection such as bit, Mud Type, applied weight on bit (WOB), Revolution per minutes (RPM), and flow rate on drilling optimization and drilling cost reduction. A predicted analysis is used in real-time drilling performance to determine the optimal drilling operation. As a result of these modeling studies, the real data collected from three directional wells at Azadegan oil fields, Iran, was verified and adjusted to determine the drillability of a specific formation. Simulation results and actual drilling results show significant improvements in inaccuracy. Once simulations had been validated, optimum drilling parameters and equipment specifications were determined by varying weight on bit (WOB), rotary speed (RPM), hydraulics (hydraulic pressure), and bit specification for each well until the highest drilling rate was achieved. To evaluate the potential operational and economic benefits of optimizing results, a qualitative and quantitative analysis of the data was performed.

Keywords: drlling, cost, optimization, parameters

Procedia PDF Downloads 170

Authors: Mohsen Torabi, Nader Karimi, Kaili Zhang

Abstract:

This work aims to provide a comprehensive study on the heat transfer and entropy generation rates of a horizontal channel partially filled with a porous medium which experiences internal heat generation or consumption due to exothermic or endothermic chemical reaction. The focus has been given to the local thermal non-equilibrium (LTNE) model. The LTNE approach helps us to deliver more accurate data regarding temperature distribution within the system and accordingly to provide more accurate Nusselt number and entropy generation rates. Darcy-Brinkman model is used for the momentum equations, and constant heat flux is assumed for boundary conditions for both upper and lower surfaces. Analytical solutions have been provided for both velocity and temperature fields. By incorporating the investigated velocity and temperature formulas into the provided fundamental equations for the entropy generation, both local and total entropy generation rates are plotted for a number of cases. Bifurcation phenomena regarding temperature distribution and interface heat flux ratio are observed. It has been found that the exothermicity or endothermicity characteristic of the channel does have a considerable impact on the temperature fields and entropy generation rates.

Keywords: entropy generation, exothermicity or endothermicity, forced convection, local thermal non-equilibrium, analytical modelling

Procedia PDF Downloads 416

Authors: Sirilak Kongkaew, Pathumwadee Yodmanee, Nopporn Kaiyawet, Arthitaya Meeprasert, Thanyada Rungrotmongkol, Toshikatsu Kaburaki, Hiroshi Noguchi, Fujio Takeuch, Nawee Kungwan, Supot Hannongbua

Abstract:

Behçet’s disease (BD) is a genetic autoimmune expressed by multisystemic inflammatory disorder mostly occurred at the skin, joints, gastrointestinal tract, and genitalia, including ocular, oral, genital, and central nervous systems. Most BD patients in Japan and Korea were strongly indicated by the genetic factor namely HLA-B*51 (especially, HLA-B*51:01) marker in HMC class I, while HLA-A*26:01 allele has been detected from the BD patients in Greek, Japan, and Taiwan. To understand the selective binding of the MICA-TM peptide towards the HLAs associated with BD, the molecular dynamics simulations were applied on the four HLA alleles (B*51:01, B*35:01, A*26:01, and A*11:01) in complex with such peptide. As a result, the key residues in the binding groove of HLA protein which play an important role in the MICA-TM peptide binding and stabilization were revealed. The Van der Waals force was found to be the main protein-protein interaction. Based on the binding free energy prediction by MM/PBSA method, the MICA-TM peptide interacted stronger to the HLA alleles associated to BD in the identical class by 7-12 kcal/mol. The obtained results from the present study could help to differentiate the HLA alleles and explain a source of Behçet’s disease.

Keywords: Behçet’s disease, MD simulations, HMC class I, autoimmune

Procedia PDF Downloads 400

Authors: Yuntao Liu, Lei Wang, Haoran Xia

Abstract:

Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

Procedia PDF Downloads 72

Authors: Saeed Ghali, Hoda El-Faramawy, Mamdouh Eissa, Michael Mishreky

Abstract:

Scale-resistant austenitic stainless steel, X45CrNiW 18-9, has been developed, and modified steels produced through partial and total nickel replacement by nitrogen. These modified steels were produced in a 10 kg induction furnace under different nitrogen pressures and were cast into ingots. The produced modified stainless steels were forged, followed by air cooling. The phases of modified stainless steels have been investigated using the Schaeffler diagram, dilatometer, and microstructure observations. Both partial and total replacement of nickel using 0.33-0.50% nitrogen are effective in producing fully austenitic stainless steels. The nitrogen contents were determined and compared with those calculated using the Institute of Metal Science (IMS) equation. The results showed great deviations between the actual nitrogen contents and predicted values through IMS equation. So, an equation has been derived based on chemical composition, pressure, and temperature at 1600oC. [N%] = 0.0078 + 0.0406*X, where X is a function of chemical composition and nitrogen pressure. The derived equation has been used to calculate the nitrogen content of different steels using published data. The results reveal the difficulty of deriving a general equation for the prediction of nitrogen content covering different steel compositions. So, it is necessary to use a narrow composition range.

Keywords: solubility, nitrogen, stainless steel, Schaeffler

Procedia PDF Downloads 239

Authors: N. Gigauri, V. Kukhalashvili, A. Surmava, L. Intskirveli, L. Gverdtsiteli

Abstract:

Tbilisi, a large city of the South Caucasus, is a junction point connecting Asia and Europe, Russia and republics of the Asia Minor. Over the last years, its atmosphere has been experienced an increasing anthropogenic load. Numerical modeling method is used for study of Tbilisi atmospheric air pollution. By means of 3D non-linear non-steady numerical model a peculiarity of city atmosphere pollution is investigated during background western light air. Dust concentration spatial and time changes are determined. There are identified the zones of high, average and less pollution, dust accumulation areas, transfer directions etc. By numerical modeling, there is shown that the process of air pollution by the dust proceeds in four stages, and they depend on the intensity of motor traffic, the micro-relief of the city, and the location of city mains. In the interval of time 06:00-09:00 the intensive growth, 09:00-15:00 a constancy or weak decrease, 18:00-21:00 an increase, and from 21:00 to 06:00 a reduction of the dust concentrations take place. The highly polluted areas are located in the vicinity of the city center and at some peripherical territories of the city, where the maximum dust concentration at 9PM is equal to 2 maximum allowable concentrations. The similar investigations conducted in case of various meteorological situations will enable us to compile the map of background urban pollution and to elaborate practical measures for ambient air protection.

Keywords: air pollution, dust, numerical modeling, urban

Procedia PDF Downloads 188

Authors: Ayu Nabila Kusuma Pradana, Aprinaldi Jasa Mantau, Tomohiko Akahoshi

Abstract:

The incidence of Disseminated intravascular coagulation (DIC) following gastrointestinal surgery has a poor prognosis. Therefore, it is important to determine the factors that can predict the prognosis of DIC. This study will investigate the factors that may influence the outcome of DIC in patients after gastrointestinal surgery. Eighty-one patients were admitted to the intensive care unit after gastrointestinal surgery in Kyushu University Hospital from 2003 to 2021. Acute DIC scores were estimated using the new Japanese Association for Acute Medicine (JAAM) score from before and after surgery from day 1, day 3, and day 7. Acute DIC scores will be compared with The Sequential Organ Failure Assessment (SOFA) score, platelet count, lactate level, and a variety of biochemical parameters. This study applied machine learning algorithms to predict the prognosis of DIC after gastrointestinal surgery. The results of this study are expected to be used as an indicator for evaluating patient prognosis so that it can increase life expectancy and reduce mortality from cases of DIC patients after gastrointestinal surgery.

Keywords: the survival rate, gastrointestinal surgery, JAAM score, neural network, machine learning, disseminated intravascular coagulation (DIC)

Procedia PDF Downloads 260

Authors: Nur A. Özdemir, Sude Erkin, Hatice K. Güney, Cemre S. Atılgan, Enes Huylu, Hüseyin Y. Altıntaş, Aysemin Top, Özak Durmuş

Abstract:

Carbon emissions produced during a product’s life cycle, from extraction of raw materials up to waste disposal and market consumption activities are the major contributors to global warming. In the light of the science-based targets (SBT) leading the way to a zero-carbon economy for sustainable growth of the companies, carbon footprint reporting of the purchased goods has become critical for identifying hotspots and best practices for emission reduction opportunities. In line with Ford Otosan's corporate sustainability strategy, research was conducted to evaluate the carbon footprint of purchased products in accordance with Scope 3 of the Greenhouse Gas Protocol (GHG). The purpose of this paper is to develop a systematic and transparent methodology to calculate carbon footprint of the products produced by automotive OEMs (Original Equipment Manufacturers) within the context of automobile supply chain management. To begin with, primary material data were collected through IMDS (International Material Database System) corresponds to company’s three distinct types of vehicles including Light Commercial Vehicle (Courier), Medium Commercial Vehicle (Transit and Transit Custom), Heavy Commercial Vehicle (F-MAX). Obtained material data was classified as metals, plastics, liquids, electronics, and others to get insights about the overall material distribution of produced vehicles and matched to the SimaPro Ecoinvent 3 database which is one of the most extent versions for modelling material data related to the product life cycle. Product life cycle analysis was calculated within the framework of ISO 14040 – 14044 standards by addressing the requirements and procedures. A comprehensive literature review and cooperation with suppliers were undertaken to identify the production methods of parts used in vehicles and to find out the amount of scrap generated during part production. Cumulative weight and material information with related production process belonging the components were listed by multiplying with current sales figures. The results of the study show a key modelling on carbon footprint of products and processes based on a scientific approach to drive sustainable growth by setting straightforward, science-based emission reduction targets. Hence, this study targets to identify the hotspots and correspondingly provide broad ideas about our understanding of how to integrate carbon footprint estimates into our company's supply chain management by defining convenient actions in line with climate science. According to emission values arising from the production phase including raw material extraction and material processing for Ford OTOSAN vehicles subjected in this study, GHG emissions from the production of metals used for HCV, MCV and LCV account for more than half of the carbon footprint of the vehicle's production. Correspondingly, aluminum and steel have the largest share among all material types and achieving carbon neutrality in the steel and aluminum industry is of great significance to the world, which will also present an immense impact on the automobile industry. Strategic product sustainability plan which includes the use of secondary materials, conversion to green energy and low-energy process design is required to reduce emissions of steel, aluminum, and plastics due to the projected increase in total volume by 2030.

Keywords: automotive, carbon footprint, IMDS, scope 3, SimaPro, sustainability

Procedia PDF Downloads 109

Authors: Stella O. Olubodun, George E. Eriyamremu

Abstract:

The study assessed the effect of crude oil applied at rates, 0, 2, 5, and 10% on the fractional chemical forms and availability of some metals in soils from Usen, Edo State, with no known crude oil contamination and soil from a crude oil spill site in Ubeji, Delta State, Nigeria. Three methods were used to determine the bioavailability of metals in the soils: maize (Zea mays) plant, EDTA and BCR sequential extraction. The sequential extract acid soluble fraction of the BCR extraction (most labile fraction of the soils, normally associated with bioavailability) were compared with total metal concentration in maize seedlings as a means to compare the chemical and biological measures of bioavailability. Total Fe was higher in comparison to other metals for the crude oil contaminated soils. The metal concentrations were below the limits of 4.7% Fe, 190mg/kg Cu and 720mg/kg Zn intervention values and 36mg/kg Cu and 140mg/kg Zn target values for soils provided by the Department of Petroleum Resources (DPR) guidelines. The concentration of the metals in maize seedlings increased with increasing rates of crude oil contamination. Comparison of the metal concentrations in maize seedlings with EDTA extractable concentrations showed that EDTA extracted more metals than maize plant.

Keywords: availability, crude oil contamination, EDTA, maize, metals

Procedia PDF Downloads 230

Authors: Sandeep Pandey, Nimra Habib, Ranjana Singh, Abbas Ali Mahdi

Abstract:

Leukemia is a malignancy of blood that mainly affects children and young adults; while advancement in the early diagnosis will have the potential to improve the outcome of diseases. A wide range of disease including leukemia shows inflammatory signals in their pathogenesis. In a pilot study conducted in our laboratory, 52 people were screened, of which 26 had leukemia and 26 were free from any kind of malignancy. We performed the estimation of the inflammatory cytokine Interleukin-8 and it was found significantly raised in all the leukemia patients concerning healthy volunteers who participated in the study. Flow cytometry had been performed for the confirmation of leukemia and further genomic, and proteomic, analyses of the sample revealed that IL-8 levels showed a positive correlation in patients with leukemia. The results had shown constitutive secretion of interleukin-8 by leukemia cells. So, our finding demonstrated that IL-8 is considered to have a role in the pathogenesis of leukemia, and quantification of IL-8 levels in leukemia conditions might be more useful and feasible in the clinical setting for the prediction of drug responses where it may represent a putative target for innovative diagnostic toward effective therapeutic approaches. However, further research explorations in this area are needed that include a greater number of patients with all different forms of leukemia, and estimating their IL-8 levels may hold the key for the additional predictive values on the recurrence of leukemia and its prognosis.

Keywords: T-ALL, IL-8, leukemia pathogenesis, cancer therapeutics

Procedia PDF Downloads 72

Authors: Faraj Ahmed E. Alhegagi, Anagia M. Khamkam Mohamed, Bassam F. Alhajaji

Abstract:

Duplex stainless steels (DSS) are widely employed in industry for apparatus working with sea water in petroleum, refineries and in chemical plants. Fracture of DSS takes place by cleavage of the ferrite phase and the austenite phase ductile tear off. Pop-in is an important feature takes place during fracture of DSS. The procedure of Pop-ins assessment plays an important role in fracture toughness studies. In present work, Zeron100 DSS specimens were heat treated at different temperatures, cooled and pulled to failure to assess the pop-ins criterion in crack initiation prediction. The outcome results were compared to the British Standard (BS 7448) and the ASTEM standard (E1290) for Crack-Tip Opening Displacement (CTOD) fracture toughness measurement. Pop-in took place during specimens loading specially for those specimens heat treated at higher temperatures. The standard BS7448 was followed to check specimen validity for fractured toughness assessment by direct determination of KIC. In most cases, specimens were invalid for KIC measurement. The two procedures were equivalent only when single pop-ins were assessed. A considerable contrast in fracture toughness value between was observed where multiple pop-ins were assessed.

Keywords: fracture toughness, stainless steels, pop ins, crack assessment

Procedia PDF Downloads 127

Authors: Isha Sharawat, R. P. Dahiya, T. R. Sreekrishnan

Abstract:

One of the environmental challenges in India is urban wastewater management as regulations and infrastructural development has not kept pace with the urbanization and growing population. The quality of life of people is also improving with the rapid growth of the gross domestic product. This has contributed to the enhancement in the per capita water requirement and consumption. More domestic water consumption generates more wastewater. The scarcity of potable water is making the situation quite serious, and water supply has to be regulated in most parts of the country during summer. This requires elaborate and concerted efforts to efficiently manage the water resources and supply systems. In this article, a system dynamics modelling approach is used for estimating the water demand and wastewater generation in a district headquarter city of North India. Projections are made till the year 2035. System dynamics is a software tool used for formulation of policies. On the basis of the estimates, policy scenarios are developed for sustainable development of water resources in conformity with the growing population. Mitigation option curtailing the water demand and wastewater generation include population stabilization, water reuse and recycle and water pricing. The model is validated quantitatively, and sensitivity analysis tests are carried out to examine the robustness of the model.

Keywords: system dynamics, wastewater, water pricing, water recycle

Procedia PDF Downloads 265

Authors: Omar Al Denali, Abdelaziz Badi

Abstract:

The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.

Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error

Procedia PDF Downloads 155

Authors: Nasir Khalid, S. Thirumalaichelvam

Abstract:

In most buildings, according to US Department of Energy Data Book, the electrical consumption attributable to centralized heating and ventilation of air- condition (HVAC) component can be as high as 40-60% of the total electricity consumption for an entire building. To provide efficient energy management for the market today, researchers are finding new ways to develop a system that can save electrical consumption of buildings even more. In this concept paper, a system known as Intelligent Chiller Energy Efficiency (iCEE) System is being developed that is capable of saving up to 25% from the chiller’s existing electrical energy consumption. In variable frequency drives (VFDs), research has found significant savings up to 30% of electrical energy consumption. Together with the VFDs at specific Air Handling Unit (AHU) of HVAC component, this system will save even more electrical energy consumption. The iCEE System is compatible with any make, model or age of centrifugal, rotary or reciprocating chiller air-conditioning systems which are electrically driven. The iCEE system uses engineering principles of efficiency analysis, enthalpy analysis, heat transfer, mathematical prediction, modified genetic algorithm, psychometrics analysis, and optimization formulation to achieve true and tangible energy savings for consumers.

Keywords: variable frequency drives, adjustable speed drives, ac drives, chiller energy system

Procedia PDF Downloads 559

Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel

Abstract:

The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.

Keywords: big data, sustainability, supply chain social sustainability, social risk, case study

Procedia PDF Downloads 410

Authors: Najrullah Khan, Athar Ali Khan

Abstract:

The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

Procedia PDF Downloads 536

Authors: Ehsan Gholamalizadeh, Jae Dong Chung

Abstract:

Solar chimney power plant is a feasible solar thermal system which produces electricity from the Sun. The objective of this study is to investigate buoyancy-driven flow and heat transfer through a built pilot solar chimney system called 'Kerman Project'. The system has a chimney with the height and diameter of 60 m and 3 m, respectively, and the average radius of its solar collector is about 20 m, and also its average collector height is about 2 m. A three-dimensional simulation was conducted to analyze the system, using computational fluid dynamics (CFD). In this model, radiative transfer equation was solved using the discrete ordinates (DO) radiation model taking into account a non-gray radiation behavior. In order to modelling solar irradiation from the sun’s rays, the solar ray tracing algorithm was coupled to the computation via a source term in the energy equation. The model was validated with comparing to the experimental data of the Manzanares prototype and also the performance of the built pilot system. Then, based on the numerical simulations, velocity and temperature distributions through the system, the temperature profile of the ground surface and the system performance were presented. The analysis accurately shows the flow and heat transfer characteristics through the pilot system and predicts its performance.

Keywords: buoyancy-driven flow, computational fluid dynamics, heat transfer, renewable energy, solar chimney power plant

Procedia PDF Downloads 264

Authors: Samatha Ss Sutton, Kaouther Kooli

Abstract:

In recent years social media influences (SMI) have become integrated into many companies marketing strategies to create buzz, target new and younger markets and further expand social media coverage in business (Lim et al 2017). SMI’s can be defined as online personalities with a substantial number of followers, across one or more social media platforms, with influence on their followers (Lou and Yuan 2018). Recently expenditure on influencer marketing has increased exponentially becoming an important area for marketing opportunities and strategies in the future (Lou and Yuan 2018). In order to market products and brands effectively through SMI’s it is important for business to understand the attributes of SMI that effect purchase intention (Lim et al 2017) of their followers and whether or not these attributes vary across generations so to market effectively to their specific segment or target market. The present study involves quantitative research to understand the attributes by which influence differs across generations namely Generation X and Millennials and its effects on purchase intentions of these generational groups. A survey will be conducted using an online questionnaire. Structural Equation Modelling and Multi group analysis will be applied. The study provides insight to marketers/decision makers on how to use influencers accordingly with their target consumer.

Keywords: social media marketing, social media influencers, attitude towards social media influencers, intention to purchase

Procedia PDF Downloads 136

Authors: Eka Yuliana, Siska Shabrina Julyan

Abstract:

The competitive environment and high customer’s churn rate in telecommunication industries lead Indonesian telecommunication companies become strive to offer products with more value. Offering product with more value can encourage customers to keep using the companies product. One of way to retain customer is give a membership card to the customers as practiced by PT. Telkom by giving Telkom Membership Card to PT. Telkom loyal customer. This study aims to determine the influence of Telkom Membership Card customer perceived value on retaining PT. Telkom Indonesia’s customer in 2013-2014 by using quantitative method with causal study. Analythical technique used in this study is Structural Equation Modelling (SEM) to test the causal relationship with 216 owner of Telkom Membership Card in Indonesia. This study conclude that: (i) Customer perceived value on Telkom Membership Card is located in fair value zone, (ii) PT. Telkom efforts in order to retain the customers is classified as good, (iii) Customer perceived value is influencing the effort to retain the customer with the probability value less than 0.05 and level of influence 69%. Based on result of this study, PT. Telkom should (i) Improve Telkom Membership Card’s promotion because not all customer of PT. Telkom have the membership card. (iia) Adding Telkom Membership Card’s benefit such as discount at various merchant (iib) Making call center for member of Telkom Membership Card (iii) PT. Telkom should be ensure availability of their service. (iv) PT. Telkom should make a priority to customer who have telkom membership card and offers a better service.For future research should be use different variables.

Keywords: customer perceived value, customer retention, marketing, relationship marketing

Procedia PDF Downloads 322

Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

Abstract:

River is our main source of water which is a form of open channel flow and the flow in open channel provides with many complex phenomenon of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress and depth averaged velocity. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, CES software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel and the results is compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth, velocity distribution

Procedia PDF Downloads 154

Authors: Sirilak Areerachakul

Abstract:

Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

Procedia PDF Downloads 345

Authors: Karl-Erich Lindenschmidt, Apurba Das, Joel Trudell, Keanne Russell

Abstract:

In this presentation, we explore options for mitigating ice-jam flooding along the Athabasca River in western Canada. Not only flood hazard, expressed in this case as the probability of flood depths and extents being exceeded, but also flood risk, in which annual expected damages are calculated. Flood risk is calculated, which allows a cost-benefit analysis to be made so that decisions on the best mitigation options are not based solely on flood hazard but also on the costs related to flood damages and the benefits of mitigation. The river ice model is used to simulate extreme ice-jam flood events with which scenarios are run to determine flood exposure and damages in flood-prone areas along the river. We will concentrate on three mitigation options – the placement of a dike, artificial breakage of the ice cover along the river, the installation of an ice-control structure, and the construction of a reservoir. However, any mitigation option is not totally failsafe. For example, dikes can still be overtopped and breached, and ice jams may still occur in areas of the river where ice covers have been artificially broken up. Hence, for all options, it is recommended that zoning of building developments away from greater flood hazard areas be upheld. Flood mitigation can have a negative effect of giving inhabitants a false sense of security that flooding may not happen again, leading to zoning policies being relaxed. (Text adapted from Lindenschmidt [2022] "Ice Destabilization Study - Phase 2", submitted to the Regional Municipality of Wood Buffalo, Alberta, Canada)

Keywords: ice jam, flood hazard, flood risk river ice modelling, flood risk

Procedia PDF Downloads 189

Authors: Samaila Bawa Muazu

Abstract:

Hydration process, crack potential and setting time of concrete grade C30, C40 and C50 were separately monitored using non-contact electrical resistivity apparatus, a novel plastic ring mould and penetration resistance method respectively. The results show highest resistivity of C30 at the beginning until reaching the acceleration point when C50 accelerated and overtaken the others, and this period corresponds to its final setting time range, from resistivity derivative curve, hydration process can be divided into dissolution, induction, acceleration and deceleration periods, restrained shrinkage crack and setting time tests demonstrated the earliest cracking and setting time of C50, therefore, this method conveniently and rapidly determines the concrete’s crack potential. The highest inflection time (ti), the final setting time (tf) were obtained and used with crack time in coming up with mathematical models for the prediction of concrete’s cracking age for the range being considered. Finally, ANSYS numerical simulations supports the experimental findings in terms of the earliest crack age of C50 and the crack location that, highest stress concentration is always beneath the artificially introduced expansion joint of C50.

Keywords: concrete hydration, electrical resistivity, restrained shrinkage crack, setting time, simulation

Procedia PDF Downloads 211

Authors: Helena Susana Afonso Alves, Natália Maria Rafael Canadas, Ana Maria Rodrigues

Abstract:

We examined the impact of governance rules on information asymmetry, using the turnover ratio and the bid-ask spread as proxies for the information asymmetry. We used a SEM model and analyzed the indirect relations through the voluntary disclosure of information and the organizational performance. We built a voluntary disclosure index based on the information firms provided in their annual reports and divided the governance characteristics in two constructs: directors’ and supervisors’ structures and ownership structure. We concluded that the ownership structure exerts a direct influence on share price and share liquidity, Otherwise, the directors’ and supervisors’ structures exert an indirect influence, through the organizational performance and the voluntary disclosure of information. The results also show that for firms with high levels of disclosure the bid-ask spread is lower. However, in firms with a high ownership concentration investors tend to increase the bid-ask spreads and trade less, which, in this case, reduces the liquidity of the stock. The failure to find the relationship between voluntary disclosure of information and the turnover ratio shows us that the liquidity of shares is more related to the greater or lesser concentration of shareholders, with the performance of their companies than with the access to information. Moreover, it is clear that the role that information disclosure plays is mainly at the level of price formation.

Keywords: corporate governance, information asymmetry, voluntary disclosure, structural equation modelling, SEM

Procedia PDF Downloads 518

Authors: Dudam Bharath Kumar, Harsh Kumar, Naveed Ahmed

Abstract:

Vehicular traffic on the road-side plays a significant role in affecting the noise pollution in most of the cities over the world. To assess the correlation of the road-traffic on noise pollution in the city environment, continuous measurements were carried out in an entire daytime starting from 8:00 AM IST to 6:00 PM IST at a single point for each 5 minutes (8:00-8:05, 9:00-9:05, 10:00-10:05 AM, ...) near the KIIT University campus road. Noise levels were observed using a mobile operated app of android cell phone and a handheld noise meter. Calibration analysis shows high correlation about 0.89 for the study location for the day time period. Results show diurnal variability of atmospheric noise pollution levels go hand-in and with the vehicular number which pass through a point of observation. The range of noise pollution levels in the daytime period is observed as 55 to 75 dB(A). As a day starts, sudden upsurge of noise levels is observed from 65 to 71 dB(A) in the early morning, 64 dB(A) in late morning, regains the same quantity 68-71 dB(A) in the afternoon, and rises 70 dB(A) in the early evening. Vehicular number of the corresponding noise levels exhibits 115-120, 150-160, and 140-160, respectively. However, this preliminary study suggests the importance of vehicular traffic on noise pollution levels in the urban environment and further to study population exposed to noise levels. Innovative approaches help curb the noise pollution through modelling the traffic noise pollution spatially and temporally over the city environments.

Keywords: noise pollution, vehicular traffic, urban environment, noise meter

Procedia PDF Downloads 297

Authors: E. A. Kiridi, A. O. Ogunlela

Abstract:

Pollutants from aquacultural practices constitute environmental problems and phytoremediation could offer cheaper environmentally sustainable alternative since equipment using advanced treatment for fish tank effluent is expensive to import, install, operate and maintain, especially in developing countries. The main objective of this research was, therefore, to develop a mathematical model for phytoremediation by aquatic plants in aquaculture wastewater. Other objectives were to evaluate the retention times on phytoremediation rates using the model and to measure the nutrient level of the aquaculture effluent and phytoremediation rates of three aquatic macrophytes, namely; water hyacinth (Eichornia crassippes), water lettuce (Pistial stratoites) and morning glory (Ipomea asarifolia). A completely randomized experimental design was used in the study. Approximately 100 g of each macrophyte were introduced into the hydroponic units and phytoremediation indices monitored at 8 different intervals from the first to the 28th day. The water quality parameters measured were pH and electrical conductivity (EC). Others were concentration of ammonium–nitrogen (NH₄⁺ -N), nitrite- nitrogen (NO₂⁻ -N), nitrate- nitrogen (NO₃⁻ -N), phosphate –phosphorus (PO₄³⁻ -P), and biomass value. The biomass produced by water hyacinth was 438.2 g, 600.7 g, 688.2 g and 725.7 g at four 7–day intervals. The corresponding values for water lettuce were 361.2 g, 498.7 g, 561.2 g and 623.7 g and for morning glory were 417.0 g, 567.0 g, 642.0 g and 679.5g. Coefficient of determination was greater than 80% for EC, TDS, NO₂⁻ -N, NO₃⁻ -N and 70% for NH₄⁺ -N using any of the macrophytes and the predicted values were within the 95% confidence interval of measured values. Therefore, the model is valuable in the design and operation of phytoremediation systems for aquaculture effluent.

Keywords: aquaculture effluent, macrophytes, mathematical model, phytoremediation

Procedia PDF Downloads 226

Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

Procedia PDF Downloads 339

Authors: F. L. Motta, M. H. A. Santana

Abstract:

Humic Acids (HA) were produced by a Trichoderma viride strain under submerged fermentation in a medium based on the oil palm Empty Fruit Bunch (EFB) and the main variables of the process were optimized by using response surface methodology. A temperature of 40°C and concentrations of 50g/L EFB, 5.7g/L potato peptone and 0.11g/L (NH4)2SO4 were the optimum levels of the variables that maximize the HA production, within the physicochemical and biological limits of the process. The optimized conditions led to an experimental HA concentration of 428.4±17.5 mg/L, which validated the prediction from the statistical model of 412.0mg/L. This optimization increased about 7–fold the HA production previously reported in the literature. Additionally, the time profiles of HA production and fungal growth confirmed our previous findings that HA production preferably occurs during fungal sporulation. The present study demonstrated that T. viride successfully produced HA via the submerged fermentation of EFB and the process parameters were successfully optimized using a statistics-based response surface model. To the best of our knowledge, the present work is the first report on the optimization of HA production from EFB by a biotechnological process, whose feasibility was only pointed out in previous works.

Keywords: empty fruit bunch, humic acids, submerged fermentation, Trichoderma viride

Procedia PDF Downloads 310